Travis Atkison's research while affiliated with University of Alabama and other places

... The purpose of this system is to address the varied needs of many businesses and departments, including but not limited to hospitals, factories, educational institutions, and the hospitality industry. thereby facilitating enhanced mobility and unrestricted physical motion (5). In addition, the widespread adoption of intelligent devices and the internet of things (IoT) has expedited the incorporation of WBANs into healthcare infrastructures. ...

... For instance, YOLOv3 [30,36,56], Faster R-CNN [16,18,39,57], and SSD [15,51,54] have been used to detect traffic signs in images and videos. In addition, some studies have explored the use of deep learning algorithms such as CNN [7,31,43,48] and LSTM [3,10,12] for traffic sign detection. Other studies have focused on feature extraction and selection methods [4,13,24] to improve the accuracy of traffic sign detection. ...

... With the growth of the national economy, the demand for automobile freight is increasing, which makes the transportation industry develop rapidly. At the same time, people have higher and higher requirements for safety [1][2][3]. They all hope that the brake performance of vehicles will be better and better, and the requirements for comfort will also be strengthened day by day. ...

... The usage of trajectory data for traffic signal control has received wide attention during the last years (Li et al., 2018;D. Ma et al., 2021;Sufian Talukder et al., 2021;Z. Yao et al., 2020). ...

... The analysis is based on data of 985 binary attributes, an additional 14 and 34 continuous attributes covering All Bordeaux (14,349 wine) and the 1855 Bordeaux datasets (1359 wines) to build a model for a wine grade category prediction. The derived BN model outperforms SVM by increasing quality classification accuracy, precision, and the F-score (Dong et al., 2021). This work aims to provide a potential scientific contribution to understanding wine quality data by applying artificial intelligence (AI) methodologies. ...

... These applications can be comfort-oriented or safetyoriented. Comfort-oriented applications aim to improve passengers' ease by offering entertainment features like weather reports and the locations of nearby facilities [7]. In contrast, safety-oriented applications enhance the protection of all road network users. ...

... 2020; Santos et al., 2021;Adário et al., 2021). A co-modalidade é um conceito baseado em um sistema de rede unificado que garantirá a utilização efetiva e sustentável de todos os modos de transporte (Skoglund & Karlsson, 2012;Islam et al., 2020). ...

... issue, authors have developed a variety of sampling approaches [10]. SMOTE variants are the most popular oversampling approaches for dealing with binary imbalanced datasets. ...

... Wineinformatics incorporates data science and wine-related datasets produced from the process of grape growing, winemaking, and wine evaluating to discover useful information for wine producers, distributors, and consumers [1,2]. Professionals generate reports to assess the final product of wines, which may include either physicochemical laboratory data or wine review evaluations. ...

... First of all, since neural networks work very well in the data set with all attributes, many other advanced neural networks, such as convolutional neural networks (CNN) [33], recurrent neural networks (RNN) [26], and long short-term memory networks (LSTM) [34], as well as deep learning [35], can be implemented and tested in similar settings. Next, since the new Computational Wine Wheel provides a stronger capability in processing wine reviews, the positive impact may also extend to all existing wineinformatics data mining research, such as research using association rules [7], clustering [9], granular computing [36], etc. Unlike this paper, which mainly focuses on classification, different data mining techniques and algorithms should be able to fine-tune the parameters and retrieve useful domain knowledge. ...